Title :
Artificial intelligence in network intrusion detection
Author :
Stampar, M. ; Fertalj, K.
Author_Institution :
Inf. Syst. Security Bur., Zagreb, Croatia
Abstract :
In past, detection of network attacks has been almost solely done by human operators. They anticipated network anomalies in front of consoles, where based on their expert knowledge applied necessary security measures. With the exponential growth of network bandwidth, this task slowly demanded substantial improvements in both speed and accuracy. One proposed way how to achieve this is the usage of artificial intelligence (AI), progressive and promising computer science branch, particularly one of its sub-fields - machine learning (ML) - where main idea is learning from data. In this paper authors will try to give a general overview of AI algorithms, with main focus on their usage for network intrusion detection.
Keywords :
computer network security; learning (artificial intelligence); AI algorithm; ML; artificial intelligence; expert knowledge; machine learning; network attacks detection; network bandwidth; network intrusion detection; Artificial intelligence; Artificial neural networks; Classification algorithms; Intrusion detection; Market research; Niobium; Support vector machines;
Conference_Titel :
Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2015 38th International Convention on
Conference_Location :
Opatija
DOI :
10.1109/MIPRO.2015.7160479